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Module code: FSS1
Credits: 5
Semester: 1 and 2
International: No
Overview Overview

This is a 4 day workshop module. The first two days will take place in semester one and will introduce students to sampling, data collection techniques, SPSS, descriptive statistics and probability. The workshop in semester two will introduce students to probability distributions, hypothesis testing and cover a selection of inferential and exploratory quantitative techniques. Each day will be split into two sessions. Each session will consist of a combination of explanation, worked examples and practical application. Skills will be consolidated by practice within class periods and a supervised assignment.
During each session students will have the opportunity to use the software to work on appropriate worksheets for that session.
An individual project will be completed by each student at the end of the module.
Assessment: 100% Continuous Assessment

Recommended Reading:
Pallant, Julie, SPSS Survival Manual
Tadhg O’Shea, Essential Statistics for Researchers

Day One: Thursday 2nd November
Morning Session:
• Introduction to Sampling / Sampling techniques
• Data (Quantitative) collection methods
• Survey Design
• Primary Data collection (Survey Monkey / Qualtrics surveying software)
• Secondary Data online sources (e.g. CSO)

Afternoon Session: Introduction to SPSS
• Coding
• Data Input / Data Import
• Data Organisation and Management
• Introduction to Statistics

Day Two: Friday 3rd November

Morning Session: Descriptive Statistics
• Measures of Central Tendency
• Measures of Dispersion
• Measures of position

Afternoon Session: Charts / Introduction to Probability
• Representing data graphically
• Introduction to Probability

Day Three: Thursday 22nd March

Morning Session: Probability Distributions and z scores
• Binomial Distribution
• Poisson Distribution
• Normal Distribution
• Z – scores

Afternoon Session: Hypothesis Testing / Confidence Intervals / z tests
• Hypothesis Testing
• Z tests
• Confidence Intervals

Day Four: Friday 23rd March

Morning Session: Inferential and Exploratory Quantitative Techniques (Part 1)
• T tests
• Anova
• Chi Square

Afternoon Session: Inferential and Exploratory Quantitative Techniques (Part 2)
• Correlation
• Regression
• Multiple Regress ion

Open Learning Outcomes
Open Teaching & Learning methods
Open Assessment
Open Repeat options
Open Timetable
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